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Our current energy systems are undergoing a significant shift from fossil carbon burning to the utilization of current sunlight.  There is the misconception that this shift also implies that we have to stop using carbon-based fuels as energy carriers.  What mix of energy carriers will be optimal for our future energy systems, and possibly more importantly what mix can we use during the next 30-40 years as we transition from fossil to renewable is still a very open question.  In this talk I will describe how we might couple renewable energy to carbon-based fuels through systems of direct air capture of CO2 and subsequent conversion.  Even within this space there is significant potential diversity of molecules that can be used, for example methanol is currently gaining favor in the shipping industry, but it could be that traditional hydrocarbons are a better fit due to the existing infrastructure.

Robotic systems have been very successful in performing tasks where the inputs are well defined and known in advance. Automotive and electronic manufacturing are the classic success stories where robotic systems have demonstrated incredible value for the industry. In unstructured manufacturing, the inputs of the system can vary significantly, but the outputs of the system are defined. Food and agriculture production are examples of this type of unstructured manufacturing problem, but traditional manufacturing is also moving in this direction as robotics move beyond welding and painting. This presentation will give examples of systems that integrate advanced perception and control technologies into robotic systems to perform complex tasks like cutting, grasping, and manipulation of objects in an unstructured environment.

There are great opportunities to apply emerging technologies, including smart sensors, spatial-temporal analysis, and Artificial Intelligence to provide energy-efficient, eco-friendly, and safe transportation solutions. Dr. Tsai will present his research team’s work on collaborating with federal and state transportation agencies, as well as multinational automobile and logistics companies. This work aims to provide an integrated solution to monitor, predict, and optimize vehicle logistics, energy-emission efficiency, and safety by studying the interaction between vehicles and the transportation infrastructure using the developed GT smart data collection and advanced computing framework.

We will dive deeper into using advanced supply chain analytics to optimize cost to service, inventory, and service level tradeoffs. This demo will show how o9’s complex platform uses performance analytics and data management combined with AI rule-based micro segmentation to provide prescriptive outputs to operational supply chain planning.

We will discuss the top challenges and supply chain disruptions o9 is seeing in the market right now, especially in these post-COVID times. o9 will share how they are solving these problems by walking through specific customer stories and giving a high overview into what makes the o9 platform the most innovative next-generation Integrated Business Planning solution on the market.

Urban air mobility (UAM) with electric vertical takeoff and landing (eVTOL) aircraft is emerging as a promising aviation market for both cargo delivery and passenger travel. The rise of UAM is being driven by the convergence of two technologies: autonomy and electric aircraft propulsion. Although promising, these technologies place limits on the discovery of viable markets, the timeline of introduction, and the design of operational paradigms. In particular, electric propulsion—when achieved with battery energy storage—is highly constraining in terms of aircraft payload, range, and speed performance and in terms of operational tempo and ground infrastructure. This talk will discuss recent work in modeling aircraft performance and operations for UAM and will highlight the challenges and opportunities in particular urban markets.

Though building a Connected Intelligent Supply Chain can seem daunting, we say Think Big, Start Small, Move Fast. To that end, the Microsoft Azure ecosystem provides platforms, products, and services to accelerate incremental building of hybrid solutions no matter the scale. From Industrial IoT to Blockchain to Modern Workplace to Business Intelligence and Visualization to Augmented Reality, Microsoft spans the entire breadth and depth of digital transformation. Finally, layering AI into these solutions to further drive insight, safety, and value has never been easier than it is today on Azure with Cognitive Services and Azure Machine Learning.

There are numerous opportunities in utilizing quantitative methods in health and humanitarian systems. There are often limited resources and multiple stakeholders in these settings, and efficient and effective decision-making is important for resource utilization as well as improved outcomes for individuals or populations. We will discuss a few examples of the applications of quantitative methods in health and humanitarian systems, such as pre-positioning inventory for disaster preparedness, post-disaster debris management, intervention strategies and resource allocation for disease management, and allocation of healthcare workers to geographic areas.

Modern warehouses, factories and supply chains are becoming enormously complex systems. Historically, the design and control of these systems has depended upon evolution and refinement over time to achieve high levels of performance. As a consequence, we do not have the legacy of engineering design that is found in digital circuits, automobiles or airplanes. But that situation is changing, albeit slowly. This talk will describe the changes that are taking place, and what they mean for our research and teaching missions.​

We will discuss a general global perspective, and then a North America focus on current and future supply chain challenges relative to infrastructure constraints. An overview of omni-channel dynamics in serving related logistics needs will also be covered. Lastly, any China/US trade tariff situations that might still be in play can be discussed.

The convergence of several technology enablers, including ubiquitous connectivity, autonomous vehicles, and sophisticated analytics, provides unique opportunities to fundamentally transform mobility in the next decade. Ride-sourcing services have already modernized taxi services but they have also increased congestion and widened inequalities in accessibility. This talk looks at mobility from a logistics and supply chain angle and presents novel on-demand mobility services that have the potential to be scalable, and sustainable, handling both the first/last mile problem and congestion. Case studies will also be presented.

 A special session where two early stage companies will talk individually about their unique characteristics/problems solved. Our speaker from Sudu will present "How startups are pushing the Future of Transportation" to discuss how technology is making its way into the transportation industry and changing the way large corporations do business. Our speaker from Autit will present "The Intelligent Manufacturing Enterprise" where we will discuss the opportunities for frontier technologies (AI/ML) to enhance Legacy ERP platforms and how Autit is leading the way with data harmonization and predictive inventory for parts in manufacturing supply chains.

The Physical Internet (PI) opens many more options to deliver goods to the end destination, thanks to interconnected services. To exploit such opportunities, routing algorithms must be developed at different levels to make the PI work. In this lecture, the levels will be defined and results obtained will be compared to traditional dedicated solutions. Two main point of views will be distinguished: the shipper (how to specify routing request) and the services provider (how to publish services and make agreements). The main PI principles will be presented as well as their impacts on algorithms, data requirements and performance. Initial results show the potential, but also uncover many research opportunities for services providers to develop new services and shippers to operate their supply chain with the PI.

In this talk we will explore the possibilities of machine learning in supply chains and logistics. We will see that modern machine learning methods, often in a black box fashion, allow us to move from model-driven decision-making to data-driven decision-making. This results in high levels of flexibility and agility, which is of ever-increasing importance in fast-paced supply chain and logistics environments. We will lay out the foundation of this paradigm and look at specifics examples from the supply chain and logistics context.

The seminar will introduce City Logistics and describe recent models developed for improving the sustainability of goods movement in Melbourne, including a collaborative freight system for suppliers distributing goods to retailers as well as a Central Business District (CBD) routing system for couriers.

Distribution systems in metropolitan regions are typically characterized by suppliers operating their own vehicle fleets, distributing only their goods to their customers on a regular basis. In sectors where there are multiple suppliers servicing common customers, there is an opportunity to develop collaborative systems and combine distribution networks to reduce the distance traveled by delivery vehicles. This can result in substantial savings in transport operating costs as well as environmental costs.

Additive manufacturing (AM) technologies build parts directly from digital data without any specialized or custom tooling. In the AM approach, a 3-D blueprint for an item can be downloaded from the cloud, and the item can be constructed immediately on-site, using 3-D printing equipment and feedstock materials. AM eliminates multiple time-consuming and expensive steps while significantly simplifying goods transport. AM will thus eliminate or reduce multiple supply chain tiers. The global supply base and the manufacturing landscape will be dramatically impacted through the increasing industrial adoption of AM. In this session, we will discuss the evolution of AM, some recent applications, and its impact as it relates to logistics and supply chain.

We will discuss the use of simulation as a tool for analyzing and improving supply chain performance. In particular, we will show how simulation can be used to (i) evaluate the effectiveness and robustness of a particular supply chain implementation, and (ii) compare the performance of competing supply chain strategies.

Supply chain models have mainly focused on understanding demand and optimizing supply networks for raw materials and finished goods. Attempts have been made to apply some of these classic models to optimize spare parts logistics. However, the most significant factors that drive demand for spare parts are often overlooked. These factors include reliability and industrial predictive analytics of equipment and machinery. Advances in sensor technology have enabled remote monitoring of geographically dispersed industrial assets, especially those that are considered critical and/or capital intensive (e.g. gas turbines, jet engines, generators, etc.). The sensor data can be used to remotely assess the state of health of the asset. This talk highlights a framework that utilizes sensor-based asset monitoring data and reliability analysis to optimize spare parts logistics and maintenance operations.

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